Positron emission tomography (PET), computed tomography (CT), single photon emission computed tomography (SPECT), and Magnetic Resonance (MR) imaging are commonly used for structural and functional imaging of the human body. These imaging technologies are widely used in medicine and can be used to identify diseases or adverse conditions of organs, tissues and other structures of the body.
In order to obtain accurate images by these methods, it is necessary to perform attenuation correction of the image data. Attenuation correction is derived from an attenuation map, which indicates the three-dimensional regions of space (i.e., “voxels” or volume elements) where photons, X-rays, or other imaging radiation is strongly absorbed. The attenuation maps contain attenuation correction coefficient factors, which are applied to acquired emission data to correct the data for the effects of attenuation at the particular location where the photons are detected.
In a prior nuclear imaging method, an extra CT scan is used to generate the attenuation map necessary for attenuation correction. An extra CT scan is undesirable because it is slow, and because it increases the radiation exposure of the patient. Alternatively, an extra PET scan can be used to generate the attenuation map. However, in this case, the PET scan for attenuation correction provides poor resolution and statistical quality.
A third known method for attenuation correction employs a magnetic resonance imaging (MRI) scan. MRI images have excellent resolution, tissue discrimination, and can be created rapidly and without additional radiation exposure. MRI offers many advantages for attenuation correction. See, for example, Kops, Qin, Mueller-Veggian, and Herzog, “Attenuation correction of PET scanning based on MR images,” IEEE Nuclear Science Symposium and Medical Imaging Conference 2006 (San Diego).
In fact, for certain clinical applications it is beneficial to combine MR imaging and PET imaging in one unit to merge the high-resolution anatomical images provided by MR with the functional information provided by PET. A combined MR/PET system is known, for example, from U.S. Pat. No. 7,218,112, assigned to Siemens Aktiengesellschaft and incorporated herein by reference in its entirety. Thus, for a combined MR/PET imaging system, it would seem logical to utilize MR-based attenuation correction to obtain the attenuation map.
However, MR imaging includes local coils to receive radio frequency (RF) signals from the body. These coils can cause inaccuracies in the attenuation correction of the PET image, since the coils would be in the field of view (FOV) of the PET scan, but would not be visible in the MR image used to acquire the attenuation correction factors. This is a significant problem for attenuation correction of emission data from a MR/PET system because accurate determination of attenuation from all objects in the PET FOV, including local MR RF coils, is essential for accurate image reconstruction.
An algorithm has been previously proposed to simultaneously estimate both an emitter concentration distribution and a linear attenuation coefficient distribution from emission data alone by alternating emission and linear attenuation coefficient update steps using an maximum likelihood-expectation maximization (MLEM-like) algorithm. This solution can be under-determined and can converge only to a local maximum of the likelihood. Generally, the method and system cannot be formulated in a way that would allow general constraints to be imposed on the solution and thus generally cannot incorporate the information available on the body coils, or other attenuating objects that may be in the field of view (FOV) during a PET scan of a MR/PET imaging system.
It would be an advance in the art to provide a method for attenuation correction in MR/PET imaging that accounts for the attenuation of PET emission data by RF coils or other objects of the MR scanner in the PET FOV, using PET emission data alone, without any transmission data or MR image data of such coils or objects. Such a method could provide more accurate attenuation correction and improve the quality of the PET images. Also, patient throughput, cost, and safety would be improved.